Abnormal Topological Organization of Human Brain Connectome in Primary Dysmenorrhea Patients Using Graph Theoretical Analysis

Abstract

Background: Accumulating studies have revealed altered brain function and structure in regions linked to sensory, pain and emotion in individuals with primary dysmenorrhea (PD). However, the changes in the topological properties of the brain's functional connectome in patients with PD experiencing chronic pain remain poorly understood.

Purpose: Our study aimed to explore the mechanism of functional brain network impairment in individuals withPD through a graph-theoretic analysis.

Material and methods: This study was a randomized controlled trial that included individuals with PD and healthy controls (HC) from June 2021 to June 2022. The experiment took place in the magnetic resonance imaging facility at Jiangxi Provincial People's Hospital. Static MRI scans were conducted on 23 female patients with PD and 23 healthy female controls. A two-sample t-test was conducted to compare the global and nodal indices between the two groups, while the Network-Based Statistics (NBS) method was utilized to explore the functional connectivity alterations between the groups.

Results: In the global index, The PD group exhibited decreased Sigma (p = 0.0432) and Gamma (p = 0.0470) compared to the HC group among the small-world network properties.(p<0.05) In the nodal index, the PD group displayed reduced betweenness centrality and increased degree centrality in the default mode network (DMN), along with decreased nodal efficiency and increased degree centrality in the visual network (VN). (P < 0.05, Bonferroni-corrected) Furthermore, in the connection analysis, PD patients showed altered functional connectivity in the basal ganglia network (BGN), VN, and DMN.(NBS corrected).

Conclusion: Our results indicate that individuals with PD showed abnormal brain network efficiency and abnormal connection within DMN, VN and BGN related to pain matrix. These findings have important references for understanding the neural mechanism of pain in PD.

Keywords: functional connectivity; graph theory; primary dysmenorrhea; resting-state functional magnetic resonance imaging.

Figure 1

The entire data processing and analysis procedure using graph theory method is depicted. Initially, time series were extracted from the fMRI data. Subsequently, the whole brain was partitioned using the Automated Anatomical Labeling (AAL) atlas. Following this, brain networks for both the primary dysmenorrhea (PD) and healthy control (HC) groups were formed. Finally, the global and nodal properties alongside the connectivity of brain networks were computed.

Figure 2

In the defined sparsity range (0.10< S< 0.05), both the PD group and the HC group showed typical small-world properties (γ=Cpreal/ Cprand>1, λ=Lpreal/Lprand≈1). Circles and squares correspond to the mean PD and hc, respectively, and error bars correspond to the standard error of the subject group in each state. The AUCs of small word properties and network efficiency are represented by histograms.

Figure 3

Significant nodal characteristics map the differences between two groups.

Figure 4

PD-related alterations in FC.